[Ed.] In 1990, at a session of the Joint Meetings of the American
Mathematical Society and the Mathematics Association of America in
Louisville KY, Professor Saunders Mac Lane served as keynote speaker
for a 50th anniversary celebration of Mathematical
Reviews. In
noting change over time within this publication, he cited two newer and
perhaps exciting extensions of the Reviews: to Mathematical Geography
and to Neural Nets. Since then, MR has noted a variety of
articles on these topics. The next set of two essays represents
some continuing attempts to combine these fields. In forging such
interdisciplinary
links, it is helpful to note not only when tools from one field shed
light on the other but also to note when they do not. Such
efforts may also suggest further direction for research for those
interested in beginning to explore these topics.

It is in the latter vein that specific commentary from John D. Nystuen
is offered below (in reference to the first of the two essays).
Nystuen's challenges:

Offer extended analysis:

Use time-series data over a longer period

Try a lagged version to consider periodicity in data

Give meteorological reasons for expecting the regression to
work or to fail

Discuss underlying theory

Justify, further, the purpose of the topic by discussing issues
such as:

At what amount of rainfall is the monsoon considered a
failure for that year?

What is the critical minimum for crops that year?

Mathematical observations suggesting further work (in reference
to Figure 2):

The predicted values seem to have an upward bias, rising to the
top of the chart. Why is that?

The actual average appears to fluctuate around 210 mm.
One would expect the predicted avaerage to be near this figure.
Why is it consistently higher and is that difference critical?